DocumentCode
2008987
Title
Artificial Neural Network for real time modelling of photovoltaic system under partial shading
Author
Di Vincenzo, Maria Carla ; Infield, David
Author_Institution
Inst. for Energy & Environ., Strathclyde Univ., Glasgow, UK
fYear
2010
fDate
6-9 Dec. 2010
Firstpage
1
Lastpage
5
Abstract
Shading caused by surrounding objects is an important issue for solar energy system design and analysis. In the special case of building integrated photovoltaic (BIPV) systems, the prediction of the partial shading is critical in order to reduce losses due to poor Maximum Power Point Tracking (MPPT). This paper will present a technique that uses Artificial Neural Network to predict the output power from a photovoltaic array in case of partial shading.
Keywords
building integrated photovoltaics; maximum power point trackers; neural nets; power engineering computing; artificial neural network; building integrated photovoltaics; maximum power point tracking; partial shading; Arrays; Artificial neural networks; Biological system modeling; Buildings; Photovoltaic systems; Power measurement; SPICE;
fLanguage
English
Publisher
ieee
Conference_Titel
Sustainable Energy Technologies (ICSET), 2010 IEEE International Conference on
Conference_Location
Kandy
Print_ISBN
978-1-4244-7192-8
Type
conf
DOI
10.1109/ICSET.2010.5684464
Filename
5684464
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